Artigos de revistas sobre o tema "Variational graph auto-Encoder (VGAE)"
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Veja os 47 melhores artigos de revistas para estudos sobre o assunto "Variational graph auto-Encoder (VGAE)".
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Hui, Binyuan, Pengfei Zhu e Qinghua Hu. "Collaborative Graph Convolutional Networks: Unsupervised Learning Meets Semi-Supervised Learning". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 04 (3 de abril de 2020): 4215–22. http://dx.doi.org/10.1609/aaai.v34i04.5843.
Texto completo da fonteDuan, Yuning, Jingdong Jia, Yuhui Jin, Haitian Zhang e Jian Huang. "Expressway Vehicle Trajectory Prediction Based on Fusion Data of Trajectories and Maps from Vehicle Perspective". Applied Sciences 14, n.º 10 (15 de maio de 2024): 4181. http://dx.doi.org/10.3390/app14104181.
Texto completo da fonteChoong, Jun Jin, Xin Liu e Tsuyoshi Murata. "Optimizing Variational Graph Autoencoder for Community Detection with Dual Optimization". Entropy 22, n.º 2 (7 de fevereiro de 2020): 197. http://dx.doi.org/10.3390/e22020197.
Texto completo da fonteMa, Weigang, Jing Wang, Chaohui Zhang, Qiao Jia, Lei Zhu, Wenjiang Ji e Zhoukai Wang. "Application of Variational Graph Autoencoder in Traction Control of Energy-Saving Driving for High-Speed Train". Applied Sciences 14, n.º 5 (29 de fevereiro de 2024): 2037. http://dx.doi.org/10.3390/app14052037.
Texto completo da fonteZhang, Jing, Guangli Wu e Shanshan Song. "Video Summarization Generation Based on Graph Structure Reconstruction". Electronics 12, n.º 23 (23 de novembro de 2023): 4757. http://dx.doi.org/10.3390/electronics12234757.
Texto completo da fonteZhang, Ying, Qi Zhang, Yu Zhang e Zhiyuan Zhu. "VGAE-AMF: A Novel Topology Reconstruction Algorithm for Invulnerability of Ocean Wireless Sensor Networks Based on Graph Neural Network". Journal of Marine Science and Engineering 11, n.º 4 (16 de abril de 2023): 843. http://dx.doi.org/10.3390/jmse11040843.
Texto completo da fontePatel, Neel, Nhat Le, Tan Nguyen, Fedaa Najdawi, Sandhya Srinivasan, Adam Stanford-Moore, Deeksha Kartik et al. "Abstract 4912: Unsupervised detection of stromal phenotypes with distinct fibrogenic and inflamed properties in NSCLC". Cancer Research 84, n.º 6_Supplement (22 de março de 2024): 4912. http://dx.doi.org/10.1158/1538-7445.am2024-4912.
Texto completo da fonteShi, Han, Haozheng Fan e James T. Kwok. "Effective Decoding in Graph Auto-Encoder Using Triadic Closure". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 01 (3 de abril de 2020): 906–13. http://dx.doi.org/10.1609/aaai.v34i01.5437.
Texto completo da fonteBehrouzi, Tina, e Dimitrios Hatzinakos. "Graph variational auto-encoder for deriving EEG-based graph embedding". Pattern Recognition 121 (janeiro de 2022): 108202. http://dx.doi.org/10.1016/j.patcog.2021.108202.
Texto completo da fonteZhan, Junjian, Feng Li, Yang Wang, Daoyu Lin e Guangluan Xu. "Structural Adversarial Variational Auto-Encoder for Attributed Network Embedding". Applied Sciences 11, n.º 5 (7 de março de 2021): 2371. http://dx.doi.org/10.3390/app11052371.
Texto completo da fonteXie, Luodi, Huimin Huang e Qing Du. "A Co-Embedding Model with Variational Auto-Encoder for Knowledge Graphs". Applied Sciences 12, n.º 2 (12 de janeiro de 2022): 715. http://dx.doi.org/10.3390/app12020715.
Texto completo da fontefathy,, Asmaa Mohamed. "Deep Embedding Data Fusion Scheme Using Variational Graph Auto-Encoder in IoT Environments". International Journal of Advanced Trends in Computer Science and Engineering 9, n.º 4 (25 de agosto de 2020): 4363–72. http://dx.doi.org/10.30534/ijatcse/2020/28942020.
Texto completo da fonteZhao, Yuexuan, e Jing Huang. "Dirichlet Process Prior for Student’s t Graph Variational Autoencoders". Future Internet 13, n.º 3 (16 de março de 2021): 75. http://dx.doi.org/10.3390/fi13030075.
Texto completo da fonteYao, Heng, Jihong Guan e Tianying Liu. "Denoising Protein–Protein interaction network via variational graph auto-encoder for protein complex detection". Journal of Bioinformatics and Computational Biology 18, n.º 03 (junho de 2020): 2040010. http://dx.doi.org/10.1142/s0219720020400107.
Texto completo da fonteZhou, Qiang, Xinjiang Lu, Jingjing Gu, Zhe Zheng, Bo Jin e Jingbo Zhou. "Explainable Origin-Destination Crowd Flow Interpolation via Variational Multi-Modal Recurrent Graph Auto-Encoder". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 8 (24 de março de 2024): 9422–30. http://dx.doi.org/10.1609/aaai.v38i8.28796.
Texto completo da fonteKarimi, Mostafa, Arman Hasanzadeh e Yang Shen. "Network-principled deep generative models for designing drug combinations as graph sets". Bioinformatics 36, Supplement_1 (1 de julho de 2020): i445—i454. http://dx.doi.org/10.1093/bioinformatics/btaa317.
Texto completo da fonteSu, Hang, Xinzheng Zhang, Yuqing Luo, Ce Zhang, Xichuan Zhou e Peter M. Atkinson. "Nonlocal feature learning based on a variational graph auto-encoder network for small area change detection using SAR imagery". ISPRS Journal of Photogrammetry and Remote Sensing 193 (novembro de 2022): 137–49. http://dx.doi.org/10.1016/j.isprsjprs.2022.09.006.
Texto completo da fonteXu, Lei, Leiming Xia, Shourun Pan e Zhen Li. "Triple Generative Self-Supervised Learning Method for Molecular Property Prediction". International Journal of Molecular Sciences 25, n.º 7 (28 de março de 2024): 3794. http://dx.doi.org/10.3390/ijms25073794.
Texto completo da fonteDu, Bing, Xiaomu Cheng, Yiping Duan e Huansheng Ning. "fMRI Brain Decoding and Its Applications in Brain–Computer Interface: A Survey". Brain Sciences 12, n.º 2 (7 de fevereiro de 2022): 228. http://dx.doi.org/10.3390/brainsci12020228.
Texto completo da fonteWang, Lei, Zejian Yuan e Badong Chen. "Learning to Generate an Unbiased Scene Graph by Using Attribute-Guided Predicate Features". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 2 (26 de junho de 2023): 2581–89. http://dx.doi.org/10.1609/aaai.v37i2.25356.
Texto completo da fonteMao, Cunli, Haoyuan Liang, Zhengtao Yu, Yuxin Huang e Junjun Guo. "A Clustering Method of Case-Involved News by Combining Topic Network and Multi-Head Attention Mechanism". Sensors 21, n.º 22 (11 de novembro de 2021): 7501. http://dx.doi.org/10.3390/s21227501.
Texto completo da fonteZhao, Mingle, Dingfu Zhou, Xibin Song, Xiuwan Chen e Liangjun Zhang. "DiT-SLAM: Real-Time Dense Visual-Inertial SLAM with Implicit Depth Representation and Tightly-Coupled Graph Optimization". Sensors 22, n.º 9 (28 de abril de 2022): 3389. http://dx.doi.org/10.3390/s22093389.
Texto completo da fonteLi, Peng, Shufang Guo, Chenghao Zhang, Mosharaf Md Parvej e Jing Zhang. "A Construction Method for a Dynamic Weighted Protein Network Using Multi-Level Embedding". Applied Sciences 14, n.º 10 (11 de maio de 2024): 4090. http://dx.doi.org/10.3390/app14104090.
Texto completo da fonteZhu, Guixiang, Jie Cao, Lei Chen, Youquan Wang, Zhan Bu, Shuxin Yang, Jianqing Wu e Zhiping Wang. "A Multi-task Graph Neural Network with Variational Graph Auto-Encoders for Session-based Travel Packages Recommendation". ACM Transactions on the Web, fevereiro de 2023. http://dx.doi.org/10.1145/3577032.
Texto completo da fonteLi, Dongjie, Dong Li e Guang Lian. "Variational Graph Autoencoder with Adversarial Mutual Information Learning for Network Representation Learning". ACM Transactions on Knowledge Discovery from Data, 22 de agosto de 2022. http://dx.doi.org/10.1145/3555809.
Texto completo da fonteYuan, Wei, Shiyu Zhao, Li Wang, Lijia Cai e Yong Zhang. "Online course evaluation model based on graph auto-encoder". Intelligent Data Analysis, 21 de março de 2024, 1–23. http://dx.doi.org/10.3233/ida-230557.
Texto completo da fonteLi, Dongjie, Dong Li e Guang Lian. "Variational Graph Autoencoder with Mutual Information Maximization for Graph Representations Learning". International Journal of Pattern Recognition and Artificial Intelligence, 8 de junho de 2022. http://dx.doi.org/10.1142/s0218001422520127.
Texto completo da fonteIwata, Hiroaki, Taichi Nakai, Takuto Koyama, Shigeyuki Matsumoto, Ryosuke Kojima e Yasushi Okuno. "VGAE-MCTS: A New Molecular Generative Model Combining the Variational Graph Auto-Encoder and Monte Carlo Tree Search". Journal of Chemical Information and Modeling, 22 de novembro de 2023. http://dx.doi.org/10.1021/acs.jcim.3c01220.
Texto completo da fonteLiu, Zhi, Yang Chen, Feng Xia, Jixin Bian, Bing Zhu, Guojiang Shen e Xiangjie Kong. "TAP: Traffic Accident Profiling via Multi-task Spatio-Temporal Graph Representation Learning". ACM Transactions on Knowledge Discovery from Data, 22 de setembro de 2022. http://dx.doi.org/10.1145/3564594.
Texto completo da fonteLi, Bo, Chen Peng, Zeran You, Xiaolong Zhang e Shihua Zhang. "Single-cell RNA-sequencing data clustering using variational graph attention auto-encoder with self-supervised leaning". Briefings in Bioinformatics 24, n.º 6 (22 de setembro de 2023). http://dx.doi.org/10.1093/bib/bbad383.
Texto completo da fonteDuy Nguyen, Viet Thanh, e Truong Son Hy. "Multimodal pretraining for unsupervised protein representation learning". Biology Methods and Protocols, 18 de junho de 2024. http://dx.doi.org/10.1093/biomethods/bpae043.
Texto completo da fonteYi, Jing, e Zhenzhong Chen. "Multi-modal Variational Graph Auto-encoder for Recommendation Systems". IEEE Transactions on Multimedia, 2021, 1. http://dx.doi.org/10.1109/tmm.2021.3111487.
Texto completo da fonteMrabah, Nairouz, Mohamed Bouguessa e Riadh Ksantini. "A contrastive variational graph auto-encoder for node clustering". Pattern Recognition, dezembro de 2023, 110209. http://dx.doi.org/10.1016/j.patcog.2023.110209.
Texto completo da fonteZhang, Yi, Yiwen Zhang, Dengcheng Yan, Shuiguang Deng e Yun Yang. "Revisiting Graph-based Recommender Systems from the Perspective of Variational Auto-Encoder". ACM Transactions on Information Systems, dezembro de 2022. http://dx.doi.org/10.1145/3573385.
Texto completo da fonteZhou, Xin, e Chunyan Miao. "Disentangled Graph Variational Auto-Encoder for Multimodal Recommendation With Interpretability". IEEE Transactions on Multimedia, 2024, 1–13. http://dx.doi.org/10.1109/tmm.2024.3369875.
Texto completo da fonteYi, Jing, Xubin Ren e Zhenzhong Chen. "Multi-Auxiliary Augmented Collaborative Variational Auto-encoder for Tag Recommendation". ACM Transactions on Information Systems, 31 de janeiro de 2023. http://dx.doi.org/10.1145/3578932.
Texto completo da fonteChen, Han, Hanchen Wang, Hongmei Chen, Ying Zhang, Wenjie Zhang e Xuemin Lin. "Denoising Variational Graph of Graphs Auto-Encoder for Predicting Structured Entity Interactions". IEEE Transactions on Knowledge and Data Engineering, 2023, 1–14. http://dx.doi.org/10.1109/tkde.2023.3298490.
Texto completo da fonteZhu, Yuan, Feng Zhang, Shihua Zhang e Ming Yi. "Predicting latent lncRNA and cancer metastatic event associations via variational graph auto-encoder". Methods, janeiro de 2023. http://dx.doi.org/10.1016/j.ymeth.2023.01.006.
Texto completo da fonteGervits, Asia, e Roded Sharan. "Predicting genetic interactions, cell line dependencies and drug sensitivities with variational graph auto-encoder". Frontiers in Bioinformatics 2 (2 de dezembro de 2022). http://dx.doi.org/10.3389/fbinf.2022.1025783.
Texto completo da fonteDing, Yulian, Xiujuan Lei, Bo Liao e Fangxiang Wu. "Predicting miRNA-Disease Associations Based on Multi-View Variational Graph Auto-Encoder with Matrix Factorization". IEEE Journal of Biomedical and Health Informatics, 2021, 1. http://dx.doi.org/10.1109/jbhi.2021.3088342.
Texto completo da fonteFu, Yao, Runtao Yang e Lina Zhang. "Association prediction of CircRNAs and diseases using multi-homogeneous graphs and variational graph auto-encoder". Computers in Biology and Medicine, novembro de 2022, 106289. http://dx.doi.org/10.1016/j.compbiomed.2022.106289.
Texto completo da fonteAftab, Rukhma, Yan Qiang, Juanjuan Zhao, Zia Urrehman e Zijuan Zhao. "Graph Neural Network for representation learning of lung cancer". BMC Cancer 23, n.º 1 (26 de outubro de 2023). http://dx.doi.org/10.1186/s12885-023-11516-8.
Texto completo da fonteNgo, Nhat Khang, e Truong Son Hy. "Multimodal Protein Representation Learning and Target-aware Variational Auto-encoders for Protein-binding Ligand Generation". Machine Learning: Science and Technology, 15 de abril de 2024. http://dx.doi.org/10.1088/2632-2153/ad3ee4.
Texto completo da fonteZhang, Yihao, Yuhao Wang, Wei Zhou, Pengxiang Lan, Haoran Xiang, Junlin Zhu e Meng Yuan. "Conversational recommender based on graph sparsification and multi-hop attention". Intelligent Data Analysis, 14 de setembro de 2023, 1–21. http://dx.doi.org/10.3233/ida-230148.
Texto completo da fonteLi, Yunyi, Yongjing Hao, Pengpeng Zhao, Guanfeng Liu, Yanchi Liu, Victor S. Sheng e Xiaofang Zhou. "Edge-Enhanced Global Disentangled Graph Neural Network for Sequential Recommendation". ACM Transactions on Knowledge Discovery from Data, 6 de fevereiro de 2023. http://dx.doi.org/10.1145/3577928.
Texto completo da fontePeng, Lihong, Liangliang Huang, Qiongli Su, Geng Tian, Min Chen e Guosheng Han. "LDA-VGHB: identifying potential lncRNA–disease associations with singular value decomposition, variational graph auto-encoder and heterogeneous Newton boosting machine". Briefings in Bioinformatics 25, n.º 1 (22 de novembro de 2023). http://dx.doi.org/10.1093/bib/bbad466.
Texto completo da fonteBhavna, Km, Azman Akhter, Romi Banerjee e Dipanjan Roy. "Explainable deep-learning framework: decoding brain states and prediction of individual performance in false-belief task at early childhood stage". Frontiers in Neuroinformatics 18 (28 de junho de 2024). http://dx.doi.org/10.3389/fninf.2024.1392661.
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